王冠
发布时间:2023-03-21   访问次数:7227


王 冠



生物工程专业:硕士生导师

生物化工专业:硕士生导师

生物与医药专业(生物工程领域):硕士生导师

  


王冠,工学博士,生物反应器工程国家重点实验室讲师,硕士生导师。入选上海市青年科技启明星(2021A类),我校青年英才培育计划2020 A类),生物工程学青椒计划2019年)。2018年毕业于我校获生物化工专业工学博士学位,同年进入我校轻工技术与工程流动站从事博士后研究工作,20207月出站担任教职。

依托生物反应器工程国家重点实验室和国家生化工程技术研究中心(上海),近年来在细胞代谢模型指导发酵过程动态调控新技术以及模型化视角下工业生物过程理性放大新方法开发等方面开展了系统性研究工作。作为项目负责人主持国家自然科学基金青年基金、国家重点研发计划子课题、上海市科技创新行动计划启明星项目、上海市科技创新行动计划自然科学基金、上海市促进人才发展专项资金(博士后日常经费)等项目;作为主要项目骨干参与中国-荷兰国际科技合作专项和多项国家自然科学基金项目等。2015年赴荷兰代尔夫特理工大学(Delft University of Technology)皇家科学院院士Prof. Joseph J. Heijnen课题组开展合作项目 “Bioreactor scale-down相关实验以及定量代谢物组学分析技术交流与学习。

近年来,在Trends in Biotechnology, Biotechnology and Bioengineering, Microbial Biotechnology, Biotechnology Journal, Journal of Biotechnology等本领域权威期刊上发表SCI收录论文20余篇,第一或通讯作者15篇,英文专著章节2章,申请中国发明专利9项。受邀担任Bioengineering专刊Design, Optimization and Scale Up of Fermentation Processes Guest editor以及该期刊Topical Advisory Panel MembersBiotechnology Journal, Journal of Biotechnology, Biochemical Engineering Journal, Process Biochemistry, Metabolites, Engineering in Life Sciences等期刊审稿人。

在学生培养上,近三年指导的研究生4人次荣获研究生国家奖学金、研究生计划外奖学金、上海市优秀毕业生等荣誉称号;指导本科生参加“挑战杯”“生命科学竞赛”“互联网+等全国性创新创业大赛,通过竞赛训练学生的科研思维和培养实践能力,目前已带领相关同学2次获上海市市级及以上奖项。


研究方向:

[1]   工业规模生物反应器流场缩放(scale-down)与细胞代谢调控机制解析

大规模生物反应器细胞运动轨迹模拟与多组学整合分析

[2]   大数据-代谢模型驱动下的生物过程智能优化与调控

基于大数据-机理融合驱动模型实现发酵过程跨尺度智能优化与调控

[3]   肿瘤细胞代谢与靶向治疗

靶向肿瘤细胞代谢并结合肿瘤药物定点智能控释系统实现自杀式肿瘤治疗

[4]   哺乳动物细胞培养过程优化与放大

基于过程分析技术(PAT)的哺乳动物细胞培养工艺开发与应用


主持或参加的科研项目或基金:

[1]   上海市青年科技启明星计划A21QA1402400),项目负责人

[2]   绿色生物制造国家重点研发计划子课题2021YFC2101103),项目负责人

[3]   绿色生物制造国家重点研发计划子课题2021YFC2101005),项目负责人

[4]   国家自然科学基金青年基金项目31900073),项目负责人

[5]   上海市自然科学基金项目19ZR1413600),项目负责人

[6]   上海市促进人才发展专项资金-博士后日常经费,项目负责人

[7]   350vip浦京集团青椒计划,项目负责人

[8]   我校基本科研业务费专项基金,项目负责人

[9]   上海市生物过程工程服务平台能力建设专项,项目骨干

[10]国家自然科学基金面上基金项目21776082),项目骨干

[11]国家自然科学基金青年基金项目21506052),项目骨干

[12]中国-荷兰国际科技合作计划2013DFG32630),项目骨干


本科与研究生教学:

[1]   本科生专业必修课,《实验数据统计分析》,16学时,1学分;

[2]   本科生专业必修课,《生物反应工程原理》(全英文),48学时,3学分;

[3]   研究生专业核心课,《生物反应器工程》,32/64学时,4学分;

[4]   研究生专业选修课,《生物反应工程》(全英文),32学时,2学分。


代表性论文(*通讯作者):  

1)一作或通讯论文

[1]    Tong Wang, Xueting Wang, Yingping Zhuang, Guan Wang*. A systematic evaluation of quenching and extraction procedures for quantitative metabolome profiling of HeLa carcinoma cell under 2D and 3D cell culture conditions. Biotechnology Journal, 2023, published online.

[2]    Qi Yang, Wenli Lin, Jiawei Xu, Nan Guo, Jiachen Zhao, Gaoya Wang, Yongbo Wang, Ju Chu, and Guan Wang*. Changes in oxygen availability during glucose-limited chemostat cultivations of Penicillium chrysogenum lead to rapid metabolite, flux and productivity responses.Metabolites, 2022, 12(1), 45.

[3]    Lin Wang, Xueting Wang, Tong Wang, Yingping Zhuang, and Guan Wang*. Multi-omics analysis defines 5-fluorouracil drug resistance in 3D HeLa carcinoma cell model. Bioresources and Bioprocessing,2021, 8(1), 1-21.

[4]    Xinxin Wang, Jiachen Zhao, Jianye Xia*, Guan Wang*, Ju Chu and Yingping Zhuang. Impact of altered trehalose metabolism on physiological response of Penicillium chrysogenum chemostat cultures during industrially relevant rapid feast/famine conditions. Processes, 2021, 9(1), 118-134.

[5]    Guan Wang*, Cees Haringa, Henk Noorman, Ju Chu, and Yingping Zhuang*. Developing a computational framework to advance bioprocess scale-up. Trends in Biotechnology, 2020, 38(8), 846-856.

[6]    Guan Wang, Cees Haringa, Wenjun Tang, Henk Noorman, Ju Chu*, Yingping Zhuang*, and Siliang Zhang. Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses. Biotechnology and Bioengineering, 2020, 117, 844-867.

[7]    Tong Wang, Lin Wang, Guan Wang*, and Yingping Zhuang*. Leveraging and manufacturing in vitro multicellular spheroid-based tumor cell model as a preclinical tool for translating dysregulated tumor metabolism into clinical targets and biomarkers. Bioresources and Bioprocessing, 2020,7(1), 1-34.

[8]    Jiachen Zhao, Guan Wang*, Ju Chu, and Yingping Zhuang. Harnessing microbial metabolomics for industrial applications. World Journal of Microbiology and Biotechnology, 2020, 36(1), 1-18.

[9]    Guan Wang*, Ju Chu, Yingping Zhuang*, Walter van Gulik, and Henk Noorman. A dynamic model-based preparation of uniformly-13C-labeled internal standards facilitates quantitative metabolomics analysis of Penicillium chrysogenum. Journal of Biotechnology, 2019, 299, 21-31.

[10]  Guan Wang, Xinxin Wang, Tong Wang, Walter van Gulik, Henk J. Noorman, Yingping Zhuang*, Ju Chu*, and Siliang Zhang. Comparative fluxome and metabolome analysis of formate as an auxiliary substrate for penicillin production under glucose-limited cultivation of Penicillium chrysogenum. Biotechnology Journal, 2019, 14(10), 1900009.

[11]  Guan Wang, Junfei Zhao, Xinxin Wang, Tong Wang, Yingping Zhuang*, Ju Chu*, Siliang Zhang, Henk J. Noorman. Quantitative metabolomics and metabolic flux analysis reveal impact of altered trehalose metabolism on metabolic phenotypes of Penicillium chrysogenum in aerobic glucose-limited chemostats, Biochemical Engineering Journal, 2019, 146: 41-51.

[12]  Guan Wang, Baofeng Wu, Junfei Zhao, Cees Haringa, Jianye Xia, Ju Chu*, Yingping Zhuang, Siliang Zhang, Joseph J. Heijnen, Walter van Gulik, Amit T. Deshmukh, Henk J. Noorman*. Power input effects on degeneration in prolonged penicillin chemostat cultures: A systems analysis at flux, residual glucose, metabolite, and transcript levels, Biotechnology and Bioengineering, 2018, 115: 114-125.

[13]  Guan Wang, Junfei Zhao, Cees Haringa, Wenjun Tang, Jianye Xia, Ju Chu*, Yingping Zhuang, Siliang Zhang, Amit T. Deshmukh, Walter van Gulik, Joseph J. Heijnen, Henk J. Noorman. Comparative performance of different scale-down simulators of substrate gradients in Penicillium chrysogenum cultures: the need of a biological systems response analysis, Microbial Biotechnology, 2018, 11: 486-497.

[14]  Guan Wang, Wenjun Tang, Jianye Xia, Ju Chu*, Henk J. Noorman, Walter van Gulik. Integration of microbial kinetics and fluid dynamics toward model-driven scale-up of industrial bioprocesses, Engineering in Life Sciences, 2015, 15: 20-29.

[15]  Guan Wang, Ju Chu*, Henk J. Noorman, Jianye Xia, Wenjun Tang, Yingping Zhuang, Siliang Zhang. Prelude to rational scale-up of penicillin production: a scale-down study, Applied Microbiology and Biotechnology, 2014, 98: 2359-2369.

2)合著论文

[16]  Li, Xinzhe, Yufeng Dong, Lu Chang, Lifan Chen, Guan Wang, Yingping Zhuang, and Xuefeng Yan*. Dynamic hybrid modeling of fuel ethanol fermentation process by integrating biomass concentration XGBoost model and kinetic parameter artificial neural network model into mechanism model. Renewable Energy, 2023, 205, 574-582.

[17]  Jianye Xia, Guan Wang, Meng Fan, Min Chen, Zeyu Wang, and Yingping Zhuang*. Understanding the scale-up of fermentation processes from the viewpoint of the flow field in bioreactors and the physiological response of strains. Chinese Journal of Chemical Engineering, 2021, 30, 178-184.

[18]  Weiqiang Cao, Guan Wang, Hongzhong Lu, Liming Ouyang*, Ju Chu, Yufei Sui, and Yingping Zhuang*. Improving cytosolic aspartate biosynthesis increases glucoamylase production in Aspergillus niger under oxygen limitation. Microbial Cell factories, 2020, 19: 1-14.

[19]  Shaohuang Shen, Guan Wang, Ming Zhang, Yin Tang, Yang Gu, Weihong Jiang, Yonghong Wang* and Yingping Zhuang*. Effect of temperature and surfactant on biomass growth and higher-alcohol production during syngas fermentation by Clostridium carboxidivorans P7. Bioresources and Bioprocessing, 2020, 7(1), 1-13.

[20]  Cees Haringa, Wenjun Tang, Guan Wang, Amit T. Deshmukh, Wouter A van Winden, Ju Chu, Walter M van Gulik, Joseph J Heijnen, Robert Mudde and Henk J Noorman*. Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model: Towards rational scale-down and design optimization, Chemical Engineering Science, 2018, 175: 12-24.

[21]  Wenjun Tang, Amit T. Deshmukh, Cees Haringa, Guan Wang, Walter van Gulik, Wouter van Winden, Matthias Reuss, Joseph J. Heijnen, Jianye Xia, Ju Chu* and Henk J. Noorman. A 9-pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum, Biotechnology and Bioengineering, 2017, 114: 1733-1743.

[22]  王冠,田锡炜,夏建业,储炬,张嗣良,庄英萍*. 大数据-模型混合驱动下生物过程优化与放大的新机遇与挑战. 生物工程学报2021, 37(3), 1004-1016.

[23]  朱紫瑜,王冠,庄英萍*. 大规模哺乳动物细胞培养工程的现状与展望. 合成生物学2021, 2, 1-23.

[24]  田锡炜,王冠,张嗣良,庄英萍*. 工业生物过程智能控制原理和方法进展. 生物工程学报2019, 35(10), 2014-2024.

[25]  赵骏飞, 王冠, 吴宝峰, 储炬*, 张嗣良. 基于土壤农杆菌转化法高效构建高产产黄青霉tps1 tps2 敲除菌株. 中国医药工业杂志2017, 48(9), 1293-1301.


撰写专著:

[1]    Guan Wang*, Cees Haringa, Ju Chu, Yingping Zhuang, Wouter van Winden and Henk Noorman. Harnessing dynamic metabolomics for bioprocess prediction and beyond.Handbook of Molecular Biotechnology, CRC press, 2023, in press.

[2]    Xia JY, Guan Wang, Jihan Lin, Yonghong Wang, Ju Chu, Yingping Zhuang, SiLiang Zhang*. Advances and practices of bioprocess scale-up. Bioreactor Engineering Research and Industrial Applications II: Springer. 2015, p 137-151.


发明专利:

[1]王冠, 王彤, 王琳, 欧阳立明, 庄英萍. 一种多细胞肿瘤球及其高通量制备方法CN110616185A

[2] 王冠, 赵佳晨, 朱慧东, 林文莉, 徐嘉蔚, 郭楠, 庄英萍. 用于工业规模生物反应器内流场环境缩放设计的方法及系统CN202210137282.4

[3] 颜学峰, 李欣喆, 董裕峰, 王冠, 常璐, 陈力凡, 田锡炜, 庄英萍. 燃料乙醇发酵过程菌丝体浓度、乙醇浓度和葡萄糖浓度时间序列预测方法CN202210921099.3

[4] 田锡炜, 常璐, 王冠, 陈力凡, 庄英萍, 张志凌, 刘晓峰, 刘劲松, 邓立康, 林海龙, 刘新颖, 邵玉彬, 田晓俊. 一种利用酿酒酵母发酵生产乙醇的方法CN202210752551.8

[5] 颜学峰, 康叶茗, 董裕峰, 卢伟鹏, 庄英萍, 邓立康, 田晓俊, 刘晓峰, 刘小辰, 张志凌, 田锡炜, 王冠, 孙新通, 范新龙, 刘新颖, 从志会. 燃料乙醇发酵过程工业知识图谱构建方法CN202110722594.7

[6] 颜学峰, 卢伟鹏, 庄英萍, 邓立康, 田晓俊, 刘晓峰, 刘小辰, 张志凌, 田锡炜, 董裕峰, 王冠, 孙新通, 范新龙, 刘新颖, 从志会. 燃料乙醇生产状态可视化在线监测方法CN202110717333.6

[7] 林海龙, 颜学峰, 董裕峰, 卢伟鹏, 刘劲松, 庄英萍, 邓立康, 田锡炜, 田晓俊, 刘晓峰, 王冠, 王梦. 发酵罐乙醇出罐浓度的预测方法、控制装置、及存储介质CN202110573442.5

[8] 田锡炜, 庄英萍, 冯瑶, 林海龙, 陈阳, 王泽宇, 王冠, 王海艺. 一种基于在线电容值监测的葡萄糖补料发酵生产乙醇的方法CN202011605264.1

[9] 田锡炜, 庄英萍, 冯瑶, 陈阳, 王泽宇, 王冠, 王海艺. 一种基于在线乙醇浓度响应值监测的葡萄糖补料发酵生产乙醇的方法CN202011606657.4


联系方式:

上海市徐汇区梅陇路130邮编200237

办公室:实验十八楼411

电话:021-64250719

邮箱:guanwang@ecust.edu.cn


 
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